optimal transport

Synergy-informed bilevel optimization reveals joint-specific benefits for realistic exoskeleton torque prediction

This study uses synergy-informed bilevel optimization to improve exoskeleton torque prediction by preventing non-physiological muscle shutdown, showing better alignment with experimental data.

Label-free flow operators and stability operators from single-cell time courses: what local dynamical operators can and cannot identify

This paper introduces scJDO2, a method to separate score and flow operators from single-cell time courses, evaluating their ability to identify unstable cells and bifurcations in hematopoiesis.

Unified cell segmentation for spatial transcriptomics via transcript reassignment

Tracel improves cell segmentation in spatial transcriptomics by assigning transcripts to cells using optimal transport, enhancing cell-type separation and reducing contamination.

LOTUS: lineage-aware optimal transport reconstructs continuous clonal fate dynamics

LOTUS reconstructs continuous clonal fate dynamics using lineage-aware optimal transport, improving lineage consistency and fate prediction in single-cell data.

Inferring scaling laws of branching networks from their geometry by global optimization

This paper uses global optimization to infer scaling laws of branching networks from their geometry, revealing type-specific signatures and outperforming existing laws in vascular systems.

Optimal Conservation Prioritization for Waterfowl and Other Birds in Eastern Canada

The paper presents an optimized geospatial prioritization scheme for bird conservation in Eastern Canada using linear programming to maximize population coverage.

GeoSinkhorn Flow: Geometry-Aware Flow Matching for Perturbation-Conditioned Dynamics in Single cell Data Phenoscapes

GeoSinkhorn Flow converts static phenoscapes into dynamic ones by learning perturbation-conditioned transport trajectories that respect the phenoscape's geometry and generalize to unseen conditions.

Optimal transport reveals unresolved cells in single cell multi-omics

This paper introduces optimal transport to explicitly reveal cell correspondences in single-cell multi-omics, improving integration and label transfer by identifying and removing ambiguous cells.

Biologically inspired alignment reveals distributed and directionally asymmetric correspondence between rat and human cortices

The paper develops BrainMapping to align rat and human cortices using resting-state fMRI, revealing distributed and directionally asymmetric correspondences between species.

Identifiable inverse optimal transport for single-cell state transitions

This paper introduces UOT-IOT, an inverse optimal transport framework for single-cell state transitions, showing improved identifiability and performance over existing methods.

Cellular Density Homeostasis Is Governed by an Anisotropic Attractor and Predictive Feedback Control

The paper identifies an anisotropic attractor and predictive feedback control mechanism governing cellular density homeostasis using single-cell mass-volume measurements.

Optogenetic BMP4 models symmetry breaking and primitive streak formation in hPSCs

This paper introduces LightBMP, an optogenetic tool to control BMP4 in hPSCs, showing spatial BMP4 patterns can drive symmetry breaking and primitive streak formation without mechanical cues.

AtlasOT - The Fused Unbalanced Gromov-Wasserstein for Multimodal Integration of Disease Atlases

AtlasOT improves multimodal integration of disease atlases by addressing unpaired data constraints through a novel optimal transport framework.

Optimizing the connectivity of protein conformations to untangle ensemble refinement

The paper introduces a method to optimize protein conformation connectivity in ensemble refinement, improving R-free and geometric accuracy in models of multiple conformations.

Mapping heterogeneity drivers in human PSC-derived limbal stem cell differentiation through single-cell multi-modal analysis

The paper uses single-cell multi-modal analysis to identify molecular drivers of limbal stem cell differentiation from human PSCs, revealing key transcription factors and enhancers involved in lineage specification.

Unsupervised alignment reveals shared but locally refined colour qualia structure from toddlerhood to adulthood

The paper uses unsupervised alignment to show that preschoolers and adults share a similar colour experience structure, while toddlers show less alignment, especially when removing late-acquired colour terms.

Optimized Multiple Circular Sequence Alignment for Cyclic Peptide Motif Discovery

The paper optimizes multiple circular sequence alignment for cyclic peptides, achieving faster performance while maintaining alignment quality.

Bayesian Efficient Coding

Letting sensory codes optimize any posterior-based loss makes information maximization (infomax) one special case; blowfly large monopolar cell responses match p = 1/2 Lp reconstruction-error codes better than infomax.

DELPHAI predicts heterogeneous perturbation responses with learned single-cell fitness

DELPHAI predicts heterogeneous perturbation responses by jointly training a fitness network and optimal transport network to identify differentially expressed genes and depleted cell lineages.

RamiGlyph Captures Microglial Morphological Diversity and Predicts Functional States in Ischemia Reperfusion and Amyloid Pathology

Accurate and scalable decontamination of imaging-based spatial transcriptomics via optimal transport

CellDot improves spatial transcriptomics by accurately decontaminating transcript assignments using optimal transport, enhancing biological interpretation and spatial pattern recovery.

DiffDose: Differentiable Programming for Personalized Dose-Regimen Optimal Control

DiffDose uses automatic differentiation to optimize drug dosing regimens by turning mechanistic PK/PD and QSP models into gradient-based tools for personalized treatment design.

Three-dimensional Virtual Adult Cardiomyocyte Transcriptomics

This paper introduces 3D-VirtualCM, a method to reconstruct full cardiomyocyte transcriptomes from spatial transcriptomic sections, revealing spatial and transcriptional heterogeneity in infarcted mouse hearts.

Cytoskeletal disassembly by optogenetic control of RhoA signaling termination

This study introduces an optogenetic tool to control RhoA signaling termination and shows it is faster than passive disactivation, revealing an asymmetry between activation and termination kinetics.

QuickSeg: A fast, versatile and accurate algorithm for genomic copy number segmentation using dynamic programming

QuickSeg improves copy number segmentation accuracy and efficiency using dynamic programming and median-based error function in cancer whole-genome sequencing data.

MOSurvivor-Guided Joint CpG Selection and XGBoost Hyperparameter Optimization for Compact Epigenetic Age Prediction

This paper introduces MOSurvivor, a multi-objective framework for selecting CpGs and optimizing XGBoost hyperparameters to predict epigenetic age with fewer features while maintaining accuracy.

Probabilistic mouse-human brain correspondence by multimodal optimal transport

OTTER maps mouse and human brain regions using optimal transport, revealing evolutionary differences in association cortex and enabling cross-species predictions.

Beyond the Default: Optimizing Molecular Networking with arteMIS

The paper introduces arteMIS, a framework for optimizing molecular network parameters in metabolomics, showing improved network quality over default settings.

Cross-Cohort Optimal Transport Maps Macrophage Plasticity and Competing Routes to Inflammation and Fibrosis in Human Atherosclerotic Plaques

The paper develops a computational framework using optimal transport to analyze macrophage state transitions in atherosclerosis, identifying origin-dependent plasticity mechanisms and shared regulatory circuits in inflammation and fibrosis.

Conditional source attribution at plankton bloom onset: Identifiability and sharp bounds under environmental forcing

The paper develops a framework to determine if plankton blooms originate internally or externally under environmental forcing, using theoretical and computational methods to assess identifiability and bounds.